Image registration, or image alignment, is the process of transforming different sets of image data into one coordinate system. The image data includes multiple images such as images from different image sensors, times, depths, viewpoints, or portions of the light spectrum. Image alignment is used in photography, computer vision, medical imaging, and compiling and analyzing images and data from telescopes and satellites, among other applications. Image alignment is used in order to be able to compare or integrate the image data obtained from these different optical measurements. Typically, image alignment occurs through intensity-based methods by comparing intensity patterns in the images via correlation metrics, or by feature-based methods by finding correspondences between image features such as points, lines, and contours. Image alignment can be accomplished at the level of pixel-by-pixel alignment, region-based registration or global registration.
One type of image alignment is stereo matching, which is used to create an illusion of depth when presenting a set of two offset images. Stereo matching is the process of determining correspondences between objects in related images, for example two images of the same image scene captured from different viewpoints. Correspondences can refer to matching points which show the same position in the image scene in both stereo images. That is, matching points represent the same portion of an object that is depicted in both stereo images. Often, determining correspondences is treated as two quite independent sub-processes, namely, segmentation, followed by matching. An image can be segmented into regions based on pixel values, for example color values or intensity values. Regions are considered as the primitives to be matched between a corresponding pair of images, since many of the shortcomings inherent in approaches based on points or lines can be overcome by matching more developed entities. The correspondences can be used for calculating the depth to an object of interest according to the principle of triangulation by using the disparity between the matching points.